Python AI Developer

We are seeking a skilled Python AI Engineer with 3 to 4 years of experience in designing, developing, and deploying AI and machine learning solutions. The ideal candidate will have strong expertise in machine learning, large language models (LLMs), data preprocessing, model training, deployment, and backend integration. This role involves close collaboration with cross-functional teams to create intelligent, scalable, and production-ready AI applications that address real-world challenges.

Key Responsibilities

- Design, develop, train, and optimize machine learning and deep learning models tailored for practical applications.
- Fine-tune and evaluate Large Language Models (LLMs) for specific domain use cases.
- Build AI-powered applications by integrating LLMs using APIs and frameworks such as LangChain or LlamaIndex.
- Perform data collection, cleaning, preprocessing, feature engineering, and exploratory data analysis (EDA).
- Develop and maintain end-to-end machine learning pipelines for training, evaluation, and deployment.
- Deploy machine learning models through REST APIs, Docker containers, and cloud platforms.
- Implement Retrieval-Augmented Generation (RAG) pipelines leveraging vector databases.
- Optimize model performance focusing on latency, scalability, and inference efficiency.
- Collaborate with software engineers and product teams to integrate AI solutions into production environments.
- Monitor model performance, retrain models as necessary, and ensure reliability in live systems.
- Stay current with advancements in AI, machine learning, and generative AI technologies.

Required Qualifications

- 3 to 4 years of professional experience in Python development and AI/ML engineering.
- Strong proficiency in Python and its AI/ML ecosystem.
- Experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch.
- Hands-on experience in training, fine-tuning, and evaluating machine learning and deep learning models.
- Familiarity with Large Language Models including OpenAI, Anthropic, Llama, Mistral, Gemini, or similar.
- Solid understanding of prompt engineering and LLM application development.
- Experience with AI orchestration frameworks like LangChain, LlamaIndex, or CrewAI.
- Strong skills in data preprocessing, cleaning, transformation, and exploratory data analysis.
- Experience working with SQL and handling both structured and unstructured datasets.
- Proficient in deploying ML models using FastAPI, Flask, or Django.
- Knowledge of vector databases such as Pinecone, Weaviate, ChromaDB, Milvus, or FAISS.
- Comfortable working with Docker, Git, and Linux environments.
- Familiarity with cloud platforms including AWS, Azure, or Google Cloud Platform.

Preferred Qualifications and Benefits

- Experience implementing Retrieval-Augmented Generation (RAG) architectures.
- Knowledge of MLOps tools such as MLflow, Kubeflow, SageMaker, or Vertex AI.
- Experience with model monitoring, versioning, and continuous deployment practices.
- Familiarity with distributed training and GPU optimization techniques.
- Experience building CI/CD pipelines for AI applications.
- Background in NLP, computer vision, or time-series forecasting is advantageous.
- Experience with workflow orchestration tools like Apache Airflow.
- Exposure to Hugging Face Transformers and PEFT/LoRA fine-tuning methods.
- Knowledge of ONNX, TensorRT, or model quantization techniques.
- Experience with Kubernetes and container orchestration.
- Familiarity with distributed data processing frameworks such as Apache Spark.
- Contributions to open-source AI projects or published research are a plus.

Education

- Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.

This role offers the opportunity to work on cutting-edge AI technologies in a collaborative environment, contributing to impactful AI-driven solutions.